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Prediction of diffuse horizontal irradiance using a new climate zone model

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  • Abreu, Edgar F.M.
  • Canhoto, Paulo
  • Costa, Maria João

Abstract

Knowledge on the diffuse horizontal irradiance (DHI), and direct normal irradiance (DNI) is crucial for the estimation of the irradiance on tilted surfaces, which in turn is critical for photovoltaic (PV) applications and for designing and simulating concentrated solar power (CSP) plants. Since global horizontal irradiance (GHI) is the most commonly measured solar radiation variable, it is advantageous for establishing a suitable method that uses it to compute DHI and DNI. In this way, a new model for predicting the diffuse fraction (Kd) based on the climate zone is proposed, using only the clearness index (Kt) as the predictor and 1-min resolution GHI data. A review of the literature on models that use hourly and sub-hourly Kt values to compute Kd was also carried out, and an extensive performance assessment of both the proposed model and the models from the literature was conducted using ten statistical indicators and a global performance index (GPI). A set of model parameters was determined for each climate zone considered in this study (arid, high albedo, temperate and tropical) using 48 worldwide radiometric stations. It was found that the best overall performing model was the model proposed in this work.

Suggested Citation

  • Abreu, Edgar F.M. & Canhoto, Paulo & Costa, Maria João, 2019. "Prediction of diffuse horizontal irradiance using a new climate zone model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 28-42.
    • Handle: RePEc:eee:rensus:v:110:y:2019:i:c:p:28-42
    DOI: 10.1016/j.rser.2019.04.055
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    1. Kaddoura, Tarek O. & Ramli, Makbul A.M. & Al-Turki, Yusuf A., 2016. "On the estimation of the optimum tilt angle of PV panel in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 626-634.
    2. Mondol, Jayanta Deb & Yohanis, Yigzaw G. & Norton, Brian, 2008. "Solar radiation modelling for the simulation of photovoltaic systems," Renewable Energy, Elsevier, vol. 33(5), pages 1109-1120.
    3. Al-Riahi, M. & Al-Hamdani, N. & Tahir, K., 1992. "An empirical method for estimation of hourly diffuse fraction of global radiation," Renewable Energy, Elsevier, vol. 2(4), pages 451-456.
    4. Despotovic, Milan & Nedic, Vladimir & Despotovic, Danijela & Cvetanovic, Slobodan, 2015. "Review and statistical analysis of different global solar radiation sunshine models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1869-1880.
    5. Hijazin, Maher I., 1998. "The diffuse fraction of hourly solar radiation for Amman/Jordan," Renewable Energy, Elsevier, vol. 13(2), pages 249-253.
    6. Elminir, Hamdy K. & Azzam, Yosry A. & Younes, Farag I., 2007. "Prediction of hourly and daily diffuse fraction using neural network, as compared to linear regression models," Energy, Elsevier, vol. 32(8), pages 1513-1523.
    7. Oliveira, Amauri P. & Escobedo, João F. & Machado, Antonio J. & Soares, Jacyra, 2002. "Correlation models of diffuse solar-radiation applied to the city of São Paulo, Brazil," Applied Energy, Elsevier, vol. 71(1), pages 59-73, January.
    8. Torres, J.L. & De Blas, M. & García, A. & de Francisco, A., 2010. "Comparative study of various models in estimating hourly diffuse solar irradiance," Renewable Energy, Elsevier, vol. 35(6), pages 1325-1332.
    9. Lee, Kwanho & Yoo, Hochun & Levermore, Geoff J., 2013. "Quality control and estimation hourly solar irradiation on inclined surfaces in South Korea," Renewable Energy, Elsevier, vol. 57(C), pages 190-199.
    10. Soares, Jacyra & Oliveira, Amauri P. & Boznar, Marija Zlata & Mlakar, Primoz & Escobedo, João F. & Machado, Antonio J., 2004. "Modeling hourly diffuse solar-radiation in the city of São Paulo using a neural-network technique," Applied Energy, Elsevier, vol. 79(2), pages 201-214, October.
    11. Marques Filho, Edson P. & Oliveira, Amauri P. & Vita, Willian A. & Mesquita, Francisco L.L. & Codato, Georgia & Escobedo, João F. & Cassol, Mariana & França, José Ricardo A., 2016. "Global, diffuse and direct solar radiation at the surface in the city of Rio de Janeiro: Observational characterization and empirical modeling," Renewable Energy, Elsevier, vol. 91(C), pages 64-74.
    12. Jacovides, C.P. & Tymvios, F.S. & Assimakopoulos, V.D. & Kaltsounides, N.A., 2006. "Comparative study of various correlations in estimating hourly diffuse fraction of global solar radiation," Renewable Energy, Elsevier, vol. 31(15), pages 2492-2504.
    13. Gueymard, Christian A., 2014. "A review of validation methodologies and statistical performance indicators for modeled solar radiation data: Towards a better bankability of solar projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1024-1034.
    14. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    15. Boland, John & Ridley, Barbara & Brown, Bruce, 2008. "Models of diffuse solar radiation," Renewable Energy, Elsevier, vol. 33(4), pages 575-584.
    16. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparative analysis of diffuse solar radiation models based on sky-clearness index and sunshine period for humid-subtropical climatic region of India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 329-355.
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